Senior Data Scientist - London

Salary: £65,000 - 105,000 per year

Requirements:

• We require a Masters or PhD in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
• We require experience in data science, machine learning, or applied NLP.
• We require strong hands-on experience with search and retrieval systems, including lexical, vector, and hybrid approaches.
• We require strong hands-on experience with RAG pipelines and LLM-based systems.
• We require strong hands-on experience with evaluation methodologies for ML, IR, and GenAI.
• We require advanced programming skills in Python.
• We require experience with modern ML/NLP frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, or Haystack.
• We require experience working with Databricks or similar distributed data and ML platforms.
• We require a strong understanding of experimentation design and statistical analysis.
• We prefer a PhD in Computer Science, Data Science, Machine Learning, or a related field.
• We prefer experience working with large-scale datasets, including scientific, biomedical, or enterprise data.
• We prefer familiarity with scientific ontologies and metadata standards such as MeSH, UMLS, ORCID, and CrossRef.
• We prefer exposure to production ML systems and MLOps practices.
• We prefer familiarity with data visualization and analytical tools such as Tableau, Power BI, matplotlib, seaborn, or similar.
• We prefer experience with human-in-the-loop evaluation or annotation workflows.
• We prefer publications or demonstrated applied research in IR, NLP, or generative AI.

Responsibilities:

• We lead the development and optimization of lexical, vector, and hybrid retrieval systems at scale.
• We help architect and improve RAG pipelines, including retrieval strategies, prompt design, and system orchestration.
• We drive experimentation with embeddings, re-ranking models, and retrieval architectures to improve relevance and user outcomes.
• We partner with engineering to ensure robust, scalable, and production-ready implementations.
• We define and evolve evaluation strategies for search and generative AI systems across our products.
• We design robust frameworks for IR evaluation, including NDCG, recall, and ranking quality.
• We design robust frameworks for GenAI evaluation, including grounding, faithfulness, and hallucination detection.
• We contribute to the development of evaluation datasets, gold standards, and annotation strategies.
• We guide and review experimental design, including offline evaluation and A/B testing, to ensure statistical rigor and validity.
• We contribute to responsible AI practices, including bias, fairness, and risk evaluation.
• We apply and adapt state-of-the-art techniques in NLP, embeddings, and generative AI to production use cases.
• We evaluate and integrate emerging technologies into our roadmap.
• We contribute to knowledge graph and semantic enrichment efforts that support retrieval systems.
• We collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems.
• We incorporate structured data, including datasets, chemical entities, genes, drugs, clinical trials, and patient outcomes, into AI-powered discovery pipelines.
• We advance our knowledge graph and metadata integration strategy to enable more context-aware retrieval.
• We apply cutting-edge research in information retrieval, NLP, embeddings, and generative AI to evolve our discovery and evaluation stack.
• We work closely with product, engineering, and domain experts to define and deliver impactful solutions.
• We communicate findings and recommendations clearly to both technical and non-technical stakeholders.
• We take ownership of projects from problem definition through experimentation and deployment.

Technologies:

• AI
• Architect
• Databricks
• Support
• LLM
• Machine Learning
• MLOps
• Power BI
• PyTorch
• Python
• RAG
• Tableau

More:

We are Elsevier, a global leader in information and analytics, helping researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. Our Search & AI Evaluation team sits within the Platform Data Science organization and advances enterprise-scale search, retrieval, and evaluation capabilities across our global products, including Scopus AI, LeapSpace, ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. We offer a culture of innovation, collaboration, and excellence, with a focus on healthy work/life balance, flexible working hours, wellbeing initiatives, shared parental leave, study assistance, sabbaticals, and a wide range of country-specific benefits. The role is full time and is based in London Wall or Amsterdam; if performed in Amsterdam, the base pay range is 53,800 - 89,900.

last updated 36 week of 2026